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We’re looking for an AI Engineer to join our team and help shape the future of data-driven GenAI solutions.
🚀 Key Responsibilities
- Design, generate, and validate synthetic datasets across multiple formats (tables, time-series, images, PDFs, JSON, Excel, CSV).
- Apply generative modeling techniques (GANs, VAEs), statistical resampling, and data masking to simulate realistic and privacy-compliant data.
- Clean, tag, classify, and enrich real or synthetic data to support risk detection, insight generation, and LLM-based decision workflows.
- Explore and evaluate new techniques for structured data extraction and data simulation, sharing insights and tools with the broader team.
- Build visualizations and dashboards to communicate results, metrics, and simulations to collaborators and stakeholders.
- Collaborate closely with AI Data Engineers and Frontend Developers to embed structured and synthetic data into GenAI applications and POCs.
- Ensure all data practices comply with privacy, regulatory, and compliance standards in partnership with legal and risk teams.
🧠 Required Skills
- Strong Python skills, with experience in libraries such as SDGym, Synthpop, Faker, or Synthea.
- Proficiency in pandas, NumPy, scikit-learn, and advanced data wrangling for structured and unstructured data.
- Hands-on experience with Jupyter-based experimentation and visualization tools (matplotlib, seaborn, Plotly).
- Familiarity with structured output tools (e.g., Pydantic, LangChain) and integrating them with LLM pipelines.
- Bonus: experience with PyTorch or TensorFlow for custom generative models.
- Comfortable working in notebook-based environments (Jupyter, Databricks) for exploration and experimentation.
- Nice to have: experience with BI tools such as Power BI, Streamlit, or Dash to build stakeholder-facing dashboards.
🥳 Benefits
💼Remote work.
💵 Salary in USD
🌐 Refund of connectivity
📚 English classes.
🎉 Birthday day
🏖️ 15 days of vacation
💳 Lunch card.
Trainings, and more!
Please share with us your English resume.
Key Skills
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